A single-tube two-color flow cytometric method for distinguishing between febrile bacterial and viral infections

Rapid detection of bacterial infection using a novel single-tube, four-colour flow cytometric method: Comparison with PCT and CRP

BACKGROUND

A key factor behind the unnecessary use of antibiotics is the lack of rapid and accurate diagnostic tests. In this study, we developed a novel and fast flow cytometric single-tube method to detect bacterial infections within 30 minutes.

METHODS

Quantitative flow cytometric four-colour analysis of host biomarkers CD35, CD64, CD329, and MHC class I expression on neutrophils and lymphocytes was performed on samples taken from 841 febrile patients with suspected infection. Obtained data was incorporated into the four-colour bacterial infection (FCBI)-index, using the developed bacterial infection algorithm.

FINDINGS

In distinguishing between microbiologically confirmed bacterial (n = 193) and viral (n = 291) infections, the FCBI-index method was superior to serum C-reactive protein (CRP) and procalcitonin (PCT). In 269 confirmed viral respiratory tract infections, 43% (95% CI: 37-49%) of the patients had an increased FCBI-index, suggesting probable bacterial coinfection.

INTERPRETATION

The proposed FCBI-index test might be a potent additional tool when assessing appropriateness of empiric antibiotic treatment.

FUNDING

This study has been financially supported by Turku University Hospital (Turku, Finland) and The Finnish Medical Foundation.

Distinguishing bacterial versus non-bacterial causes of febrile illness - A systematic review of host biomarkers

BACKGROUND

Acute febrile illnesses (AFIs) represent a major disease burden globally; however, the paucity of reliable, rapid point-of-care testing makes their diagnosis difficult. A simple tool for distinguishing bacterial versus non-bacterial infections would radically improve patient management and reduce indiscriminate antibiotic use. Diagnostic tests based on host biomarkers can play an important role here, and a target product profile (TPP) was developed to guide development.

OBJECTIVES

To qualitatively evaluate host biomarkers that can distinguish bacterial from non-bacterial causes of AFI.

DATA SOURCES

The PubMed database was systematically searched for relevant studies published between 2015 and 2019.

STUDY ELIGIBILITY CRITERIA

Studies comparing diagnostic performances of host biomarkers in patients with bacterial versus non-bacterial infections were included.

PARTICIPANTS

Studies involving human participants and/or human samples were included.

METHODS

We collected information following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A risk of bias assessment was performed, based on a modified QUADAS-2 (Quality Assessment of Diagnostic Accuracy Score 2).

RESULTS

We identified 1107 publications. Following screening, 55 publications were included, with 265 biomarker entries. Entries mostly comprised protein biomarkers (58.9%), followed by haematological, RNA, and metabolite biomarkers (15.5%, 8.7%, 12.5%). Sensitivity/specificity was reported for 45.7% of biomarker entries. We assessed a high overall risk of bias for most entries (75.8%). In studies with low/medium risk of bias, four biomarker entries tested in blood samples had sensitivity/specificity of more than 0.90/0.80. Only 12 additional biomarker entries were identified with sensitivity/specificity of more than 0.65/0.65.

CONCLUSIONS

Most recently assessed biomarkers represent well-known biomarkers, e.g. C-reactive protein and procalcitonin. Some protein biomarkers with the highest reported performances include a combined biomarker signature (CRP, IP-10, and TRAIL) and human neutrophil lipocalin (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise. Further high-quality studies are needed to confirm these findings.

Differential expression of CD64 in patients with Mycobacterium tuberculosis infection: A potential biomarker for clinical diagnosis and prognosis

To evaluate the clinical utility of neutrophil (n)CD64 index to diagnose pulmonary tuberculosis (PTB) and extrapulmonary TB (ePTB) and to predict the outcome of Mycobacterium tuberculosis infection. We recruited 189 patients with active TB and 140 controls and measured the differential expression of nCD64 index using flow cytometry. The receiver operating characteristics (ROC) curve analysis was performed to estimate the diagnostic performance of the nCD64 index and T‐SPOT.TB assay for the diagnosis of TB. Furthermore, we analysed whether the nCD64 index in patients with TB was correlated with inflammatory indicators. Finally, we assessed the prognosis of patients by following the dynamic changes of the nCD64 index once a week. The nCD64 index was significantly higher in active TB group (PTB and ePTB), than in the anti‐TB and healthy controls (HC) groups. The sensitivity and specificity of nCD64 index for the differential diagnosis of PTB and pneumonia (PN) patients were 68.33% and 77.55%, respectively. The sensitivity and specificity of nCD64 index for the diagnosis of tuberculous meningitis (TBM) were 53.85% and 100%, respectively. Furthermore, there was a weak correlation between the nCD64 index and inflammatory indicators. More importantly, with the improvement in patient condition, the nCD64 index started to decline in the first week of anti‐TB therapy and significantly decreased at 4 weeks after treatment. Our study demonstrated that the CD64 assay is a rapid, non‐invasive and stable method for clinical application, and the nCD64 index can serve as a potential biomarker for the diagnosis and prognosis of TB.